This study has investigated the underlying mechanism for social cognitive development. Inspired by neuroscience and cognitive science studies, we have suggested sensorimotor predictive learning as a principle for cognitive development and constructed computational models using neural networks and probabilistic models to verify the principle. Our experiments using robots demonstrated how predictive learning leads to development of various types of cognitive functions. For example, our robots improved the ability to recognize others’ actions based on the ability to produce own actions, generated helping behaviors through the minimization of prediction error, and acquired the ability to recognize and generate emotions through multimodal predictive learning. These results yield new insights into underlying mechanisms for human cognitive development.